Search Results

Real-time simulation of truck and trailer combinations can be applied to hardware-in-the-loop (HIL) systems for developing and testing electronic control units (ECUs). The large number of configuration variations in vehicle and axle types requires the simulation model to be adjustable in a wide range. This paper presents a modular multibody approach for the vehicle dynamics simulation of single track configurations and truck-and-trailer combinations. The equations of motion are expressed by a new formula which is a combination of Jourdain's principle and the articulated body algorithm. With the proposed algorithm, a robust model is achieved that is numerically stable even at handling limits. Moreover, the presented approach is suitable for modular modeling and has been successfully implemented as a basis for various system definitions. As a result, only one simulation model is needed for a large variety of track and trailer types.

Advanced driver assistance systems (ADAS) are becoming increasingly important for today's commercial vehicles. It is therefore crucial that different ADAS functionalities interact seamlessly with existing electronic control unit (ECU) networks. For example, autonomous emergency braking (AEB) systems directly influence the brake ECU and engine control. It has already become impossible to reliably validate this growing interconnectedness of control interventions in vehicle behavior with prototype vehicles alone. The relevant tests must be brought into the lab at an earlier development stage to evaluate ECU interaction automatically. This paper presents an approach for using hardware-in-the-loop (HIL) simulation to validate ECU networks for extremely diverse ADAS scenarios, while taking into account real sensor data. In a laboratory environment, the sensor systems based on radars, cameras, and maps are stimulated realistically with a combination of simulation and animation.

The complexity of automobile powertrains grows continuously. At the same time, development time and budget are limited. Shifting development tasks to earlier phases (frontloading) increases the efficiency by utilizing test benches instead of prototype vehicles (road-to-rig approach). Early system verification of powertrain components requires a closed-loop coupling to real-time simulation models, comparable to hardware-in-the-loop testing (HiL). The international research project Advanced Co-Simulation Open System Architecture (ACOSAR) has the goal to develop a non-proprietary communication architecture between real-time and non-real-time systems in order to speed up the commissioning process and to decrease the monetary effort for testing and validation. One major outcome will be a generic interface for coupling different simulation tools and real-time systems (e.g. HiL simulators or test benches).

In the aerospace industry, methods for virtual testing cover an increasing range of test executions carried out during the development and test process of avionics systems. Over the last years, most companies have focused on questions regarding the evaluation and implementation of methods for virtual testing. However, it has become more and more important to seamlessly integrate virtual testing into the overall development process. For instance, a company’s test strategy might stipulate a combination of different methods, such as SIL and HIL simulation, in order to benefit from the advantages of both in the same test process. In this case, efforts concentrate on the optimization of the overall process, from test specification to test execution, as well as the test result evaluation and its alignment with methods for virtual testing.

Real-time simulation of truck and trailer combinations can be applied to hardware-in-the-loop (HIL) systems for developing and testing electronic control units (ECUs). The large number of configuration variations in vehicle and axle types requires the simulation model to be adjustable in a wide range. This paper presents a modular multibody approach for the vehicle dynamics simulation of single track configurations and truck-and-trailer combinations. The equations of motion are expressed by a new formula which is a combination of Jourdain's principle and the articulated body algorithm. With the proposed algorithm, a robust model is achieved that is numerically stable even at handling limits. Moreover, the presented approach is suitable for modular modeling and has been successfully implemented as a basis for various system definitions. As a result, only one simulation model is needed for a large variety of track and trailer types.

The application of a communication infrastructure for hybrid test systems is currently a topic in the aerospace industry, as also in other industries. One main reason is flexibility. Future laboratory tests means (LTMs) need to be easier to exchange and reuse than they are today. They may originate from different suppliers and parts of them may need to fulfill special requirements and thus be based on dedicated technologies. The desired exchangeability needs to be achieved although suppliers employ different technologies with regard to specific needs. To achieve interoperability, a standardized transport mechanism between test systems is required. Designing such a mechanism poses a challenge as there are several different types of data that have to be exchanged. Simulation data is a prominent example. It has to be handled differently than control data, for example. No one technique or technology fits perfectly for all types of data.

This paper will first introduce and classify the basic principles of architecture-driven software development and will briefly sketch the presumed development process. This background information is then used to explain extensions which enable current behavior modeling and code generation tools to operate as software component generators. The generation of AUTOSAR software components using dSPACE's production code generator TargetLink is described as an example.

Today, hardware-in-the-loop (HIL) simulation is common practice as a testing methodology for electronic control units (ECUs). An essential criterion for the efficiency of an HIL system is the availability of powerful test automation having access to all of its hardware and software components (including I/O channels, failure insertion units, bus communication controllers and diagnostic interfaces). The growing complexity of vehicle embedded systems, which are interconnected by bus systems (like CAN, LIN or FlexRay), result in hundreds or even thousands of tests that have to be done to ensure the correct system functionality. This is best achieved by automated testing. Automated testing usually is performed by executing tests on a standard PC, which is interconnected to the HIL system. However, higher demands regarding timing precision are hard to accomplish. As an example, ECU interaction has to be captured and responded to in the range of milliseconds.

Due to tougher legislation on exhaust emissions reduction and the consumer demand for more power and mobility and less fuel consumption, the functionality in today's engine management systems continues to grow. The electronic engine control units (ECUs) have to perform more control tasks using new sensors and actuators, along with the corresponding self-diagnostics (OBD, on-board diagnosis). All this leads to continuously increasing demands on automated hardware-in-the-loop (HIL) test systems. HIL technology has advanced in parallel to the ECUs, and is today an indispensable tool for developing automotive electronics. This paper therefore aims to provide a comprehensive and state-of-the-art survey of HIL test systems for engine controllers. First of all, a brief introduction to the ECU's functionality is given.

Electric drives are growing in importance in automotive applications, especially in hybrid electric vehicles (HEV) and in the vehicle dynamics area (steering systems, etc.). The challenges of real-time hardware-in-the-loop (HIL) simulation and testing of electric drives are addressed in this paper. In general, three different interface levels between the electric drive and the hardware-inthe-loop system can be distinguished: the signal level (1), the electrical level (2) and the mechanical level (3). These interface levels, as well as modeling and I/O-related aspects of electric drives and power electronics devices, are discussed in detail in the paper. Finally, different solutions based on dSPACE simulator technology are presented, for both hybrid vehicle and steering applications.

Validating control units with hardware-in-the-loop (HIL) simulators is an established method for quality enhancements in automotive software. It is primarily used for testing applications, but in view of increased networking between electronic control units, it can also be used for testing communication scenarios. The testing of electronic control unit (ECU) communication often includes only positive testing. Simple communication nodes are used for this, and communication analyzers are used for verifying communication up to the physical level. However, it is not only an ECU's positive communication behavior that has to be tested, but also its correct behavior in the event of communication errors. In HIL communication scenarios, it is not only possible to emulate the missing bus nodes (restbus simulation) with a link to real-time signals; correct ECU behavior in the event of communication errors can also be tested.

In modern vehicles the architecture of electronics is growing more and more complex because both the number of electronic functions – e.g. implemented as software modules – as well as the level of networking between electronic control units (ECUs) is steadily increasing. This complexity leads to greater propagation of failure symptoms, and diagnosing the causes of failure becomes a new challenge. Diagnostics aims at detecting failures such as defect sensors or faulty communication messages. It is subdivided into diagnosis algorithms on an ECU and algorithms running offboard, e.g. on a diagnostic tester. These algorithms have to complement each other in the best possible way. While in the past the diagnosis algorithm was developed late in the development process, nowadays there are efforts to start the development of such algorithms earlier – at least in parallel to developing a new feature itself. This would allow developers to verify the diagnosis algorithms in early design stages.

Model-based development and autocoding have become common practice in the automotive industry over the past few years. The industry is using these methods to tackle a situation in which complexity is constantly growing and development times are constantly decreasing, while the safety requirements for the software stay the same or even increase. The debate is no longer whether these methods are useful, but rather on the conditions for achieving optimum results with them. From the experiences made during the last decade this paper shows some of the key factors helping to achieve success when introducing or extending the deployment of automatic code generation in a model-based design process.

Hardware-in-the-loop (HIL) testing is used by commercial vehicle original equipment manufacturers (OEMs) in several fields of electronics development. HIL tests are a part of the standard development process for engine and machine control systems. For electronic control units (ECUs), not only the HIL test of the hardware but also the controller software validation is very important. For hardware diagnostics validation, a dynamic simulation of the real system could be omitted and an open-loop test of the controller is sufficient in most cases. For most controller software validation including OBD (on-board diagnosis) tests, detailed but real-time capable models have to be used. This article describes the needs and challenges of models in hardware-in-the-loop (HIL) based testing, taking into account the wide range of commercial and off-highway vehicles.

Hardware-in-the-loop (HIL) simulation in the development and test process of vehicle dynamics controllers requires a real-time tractor-trailer simulation model. The hitch coupling must be numerically stable to ensure real-time simulation for various driving maneuvers, particularly at the vehicle's handling limits. This paper presents a robust implementation of tractor-trailer coupling. The equation of motion is formed using a novel formulation which is a combination of Jourdain's Principle and the Articulated Body Algorithm. The paper shows that a robust model for a real-time tractor-trailer simulation can be achieved with the proposed method. Moreover, the approach presented is suitable for modular modeling, is successfully implemented and can also be used as a basis for flexible system definition with an adjustable number of trailer axles.

This presentation focuses on several examples of partnerships between tool suppliers and embedded software developers in which state-of-the-art tools are used to optimize a variety of electric and hybrid vehicle architectures. Projects with Automotive OEMs, Tier One Suppliers as well as with academic institutions will be described. Due to the growing complexity in multiple electronic control units (“ECUs”) inter-communicating over numerous network bus systems, combined with the challenge of controlling and maintaining charges for electric motors, vehicle development would be impossible without use of increasingly sophisticated tools. Hybrid drive trains are much more complex than conventional ones, they have at least one degree of freedom more.

Permanently increasing software complexity of today's electronic control units (ECUs) makes testing a central and significant task within embedded software development. While new software functions are still being developed or optimized, other functions already undergo certain tests, mostly on module level but also on system and integration level. Testing must be done as early as possible within the automotive development process. Typically ECU software developers test new function modules by stimulating the code with test data and capturing the modules' output behavior to compare it with reference data. This paper presents a new and systematic way of testing embedded software for automotive electronics, called MTest. MTest combines the classical module test with model-based development. The central element of MTest is the classification-tree method, which has originally been developed by the DaimlerChrysler research department.

This paper presents an overview of a project called “Modelling and Simulation Tools for Systems Integration on Aircraft (MISSION)”. This is a collaborative project being developed under the European Union Clean Sky 2 Program, a public-private partnership bringing together aeronautics industrial leaders and public research organizations based in Europe. The provision of integrated modeling, simulation, and optimization tools to effectively support all stages of aircraft design remains a critical challenge in the Aerospace industry. In particular the high level of system integration that is characteristic of new aircraft designs is dramatically increasing the complexity of both design and verification. Simultaneously, the multi-physics interactions between structural, electrical, thermal, and hydraulic components have become more significant as the systems become increasingly interconnected.

Increasing diagnosis capabilities in modern engine electronic control units (ECUs), especially in the exhaust path, in terms of emission and engine aftertreatment control utilize on-board NOx prediction models. Nowadays it is an established approach at hardware-in-theloop (HIL) test benches to replicate the engine's steady-state NOx emissions on the basis of stationary engine data. However, this method might be unsuitable for internal ECU plausibility checks and ECU test conditions based on dynamic engine operations. Examples of proven methods for modeling the engine behavior in HIL system applications are so-called mean value engine models (MVEMs) and crank-angle-synchronous (in-cylinder) models. Of these two, only the in-cylinder model replicates the engine’s inner combustion process at each time step and can therefore be used for chemical-based emission simulation, because the formation of the relevant gas species is caused by the inner combustion states.

Hybrid test systems are gaining more and more significance in the aerospace industry. At the heart of these systems is a standardized communication infrastructure. There are many challenges when designing the communication infrastructure. For example, it requires very specific knowledge to boot a hybrid system, manage its configuration process, and start and stop the execution of applications, such as simulations, panels or recorders. Likewise, when testers use a heterogeneous test environment, they cannot commit themselves too much to every single test means and its special characteristics. Nevertheless, testers must always be able to monitor and control every test system. This means, they must be able to determine the current overall system status and the current status of its components and parts. Examples for this are hardware components, such as real-time processors and I/O boards, as well as software applications, such as real-time simulations models on the test system.